Evidence map›Paper›PMID 35068077›Full record

ArticleObesity (Silver Spring, Md.)2022

Neighborhood walkability and poverty predict excessive gestational weight gain: A cross-sectional study in New York City.

Eliza W Kinsey, Elizabeth M Widen, James W Quinn, Mary Huynh, Gretchen Van Wye, Gina S Lovasi, Kathryn M Neckerman, Andrew G Rundle

Open access · greenAbstract read
In one paragraph

Article in Obesity (Silver Spring, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Eliza W KinseyDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.ORCID 0000-0003-4972-431X
Elizabeth M WidenDepartment of Nutritional Sciences and Population Research Center, University of Texas at Austin, Austin, Texas, USA.ORCID 0000-0002-9574-6109
James W QuinnDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.
Mary HuynhBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, New York, USA.
Gretchen Van WyeBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, New York, USA.
Gina S LovasiEpidemiology and Biostatistics, Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, USA.
Kathryn M NeckermanColumbia Population Research Center, Columbia University, New York, New York, USA.
Andrew G RundleDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.ORCID 0000-0003-0211-7707
Columbia University · USNew York City Department of Health and Mental Hygiene · USDrexel University · USThe University of Texas at Austin · US

Funding

Population Research CenterR24HD042849 · NICHD · UNIVERSITY OF TEXAS AUSTIN · PI HAYWARD, MARK D. · 2002 to 2016
$8.4M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI Catherine A Calder · 2017 to 2026
$5.2M
Pregnancy weight trajectories and offspring adiposityR00HD086304 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI WIDEN, ELIZABETH MARIE · 2018 to 2020
$744k
Impacts of Early Life Food Insecurity on Child Obesity and Cognitive Development TrajectoriesR00HD101657 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI KINSEY, ELIZA W. · 2022 to 2024
$651k
Impacts of Early Life Food Insecurity on Child Obesity and Cognitive Development TrajectoriesK99HD101657 · NICHD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KINSEY, ELIZA W. · 2020 to 2021
$261k
NICHD NIH HHS K99 HD101657NICHD NIH HHS P2C HD042849NICHD NIH HHS R00 HD086304NICHD NIH HHS R00 HD101657NICHD NIH HHS R24 HD042849NIDDK NIH HHS P30 DK111022
6 · The paper itself

Abstract

objectiveThis study evaluated associations between neighborhood-level characteristics and gestational weight gain (GWG) in a population-level study of 2015 New York City births.

methodsGeneralized linear mixed-effects models were used to estimate odds ratios (ORs) for associations between neighborhood-level characteristics (poverty, food environment, walkability) within 1 km of a residential Census block centroid and excessive or inadequate GWG compared with recommended GWG. All models were adjusted for individual-level sociodemographic characteristics.

resultsAmong the sample of 106,285 births, 41.8% had excessive GWG, and 26.3% had inadequate GWG. Residence in the highest versus lowest quartile of neighborhood poverty was associated with greater odds of excessive GWG (OR: 1.17, 95% CI: 1.08-1.26). Residence in neighborhoods in the quartile of highest walkability compared with the quartile of lowest walkability was associated with lower odds of excessive GWG (OR: 0.87, 95% CI: 0.81-0.93). Adjustment for prepregnancy BMI attenuated the associations for neighborhood poverty, but not for walkability. Neighborhood variables were not associated with inadequate GWG.

conclusionsThese analyses indicate that greater neighborhood walkability is associated with lower odds of excessive GWG, potentially from differences in pedestrian activity during pregnancy. This research provides further evidence for using urban design to support healthy weight status during pregnancy.

Indexed as

Gestational Weight GainBody Mass IndexCross-Sectional StudiesFemaleHumansNew York CityPovertyPregnancy

Identifiers

PMID35068077
PMCPMC8830702
OpenAlexW4206897208

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.